Skip to main content

and
  1. No Access

    Article

    Deep learning model for predicting the presence of stromal invasion of breast cancer on digital breast tomosynthesis

    To develop a deep learning (DL)-based algorithm to predict the presence of stromal invasion in breast cancer using digital breast tomosynthesis (DBT). Our institutional review board approved this retrospective...

    Daiki Shimokawa, Kengo Takahashi, Ken Oba in Radiological Physics and Technology (2023)

  2. No Access

    Article

    Deep learning model for breast cancer diagnosis based on bilateral asymmetrical detection (BilAD) in digital breast tomosynthesis images

    The purpose of this study was to develop a deep learning model to diagnose breast cancer by embedding a diagnostic algorithm that examines the asymmetry of bilateral breast tissue. This retrospective study was...

    Daiki Shimokawa, Kengo Takahashi, Daiya Kurosawa in Radiological Physics and Technology (2023)